I recently attended .conf2016, Splunk’s seventh annual user conference. Splunk created the market for analyzing machine data (shorthand for machine-generated data), which consists of log files and event data from various types of systems and devices. Our big data analytics benchmark research shows that these are two of the most common sources of big data that organizations analyze. This market has proven to be fertile ground for Splunk, growing steadily with revenues more than doubling over the previous two fiscal years. Machine data is also the backbone for the Internet of Things (IoT) and operational intelligence, which form the basis of forthcoming benchmark research from Ventana Research.
Splunk may be one of the biggest software companies you’ve never heard of. I’ve been following the seven-year-old company for over six months now and recently attended its second annual user conference. Splunk focuses on analyzing large volumes of machine-generated data in underlying applications and systems, which includes application and system logs, network traffic, sensor data, click streams and other loosely structured information sources. Many of these “big data” sources are the same sources analyzed with Hadoop, according to our recently published benchmark research. However, Splunk takes a different approach that focuses on performing simple analyses on this data in real time rather than the batch-based advanced analytics we see as the most common use for Hadoop.
Topics: Big Data, Predictive Analytics, Sales Performance, Social Media, Supply Chain Performance, Business Analytics, Business Intelligence, Business Performance, Customer & Contact Center, Machine data, Operational Intelligence, IT Performance Management (ITPM)